Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: determining information associated with a camera of an aerial vehicle, the information including a length of a footprint of the camera and a width of the footprint of the camera, the length of the footprint being based on a horizontal component of a field of view (FOV) and an altitude of the camera and the width of the footprint being based on a vertical component of the field of view (FOV) and the altitude of the camera; determining a localized map based on the information associated with the camera; and overlaying the localized map on a vector map.
Aerial vehicle camera footprint mapping and map overlay. This invention relates to systems and methods for generating and displaying localized maps for aerial vehicles. The problem addressed is the need to accurately represent the area captured by an aerial vehicle's camera and to integrate this information with existing navigation maps. The method involves first determining information about the camera's footprint on the ground. This footprint's dimensions, specifically its length and width, are calculated based on the camera's field of view (FOV) and its altitude. The length of the footprint is derived from the horizontal component of the FOV and the altitude, while the width is derived from the vertical component of the FOV and the altitude. Once this camera footprint information is established, a localized map is generated using this data. This localized map, representing the area currently visible to the camera, is then overlaid onto a broader vector map. This overlay provides the aerial vehicle operator with a clear visual representation of the camera's coverage area in the context of the overall navigation environment.
2. The method of claim 1 , wherein the vector map includes at least one of a road network, railroad network, airport, elevation contour, coastline, boundary, or index of geographical names.
3. The method of claim 1 , wherein determining information associated with the camera of the aerial vehicle comprises: receiving sensor data from the aerial vehicle; determining the altitude of the camera based on the sensor data; determining the information associated with the camera based on the altitude of the camera and the FOV of the camera; and determining the footprint of the camera based on the information associated with the camera.
This invention relates to aerial imaging systems, specifically methods for determining camera footprint information for an aerial vehicle. The problem addressed is the need to accurately calculate the area captured by a camera mounted on an aerial vehicle, which is essential for tasks such as mapping, surveillance, and inspection. The solution involves dynamically determining the camera's footprint based on real-time sensor data and camera specifications. The method begins by receiving sensor data from the aerial vehicle, which includes altitude information. The altitude of the camera is then determined from this sensor data. Using the camera's altitude and its field of view (FOV), the system calculates the camera's information, which includes parameters like focal length and sensor dimensions. Finally, the footprint—the area on the ground covered by the camera's field of view—is determined based on the derived camera information. This ensures precise coverage calculations regardless of the vehicle's altitude or camera settings. The approach improves upon prior methods by dynamically adjusting the footprint calculation based on real-time altitude data, enhancing accuracy for applications requiring precise aerial imaging. The system can be integrated into drones, aircraft, or other aerial platforms to optimize imaging tasks.
4. The method of claim 3 , wherein determining the localized map based on the information associated with the camera comprises: receiving images from the camera; and determining the localized map based on the images and the footprint of the camera.
5. The method of claim 4 , further comprising: de-warping the images.
A method for processing images, particularly in the context of optical imaging systems, addresses distortions that occur during image capture. These distortions, often caused by lens aberrations or non-linear optical effects, result in warped or geometrically inaccurate images. The method includes a step of de-warping the images to correct these distortions, restoring the original geometric integrity of the captured visual data. This correction process involves analyzing the distortion patterns in the images and applying inverse transformations to reverse the warping effects. The de-warping step may utilize mathematical models, such as polynomial or spline-based corrections, or machine learning techniques trained on known distortion patterns. By removing these distortions, the method enhances image quality, accuracy, and usability in applications like medical imaging, surveillance, or augmented reality, where precise spatial representation is critical. The de-warping process can be applied to individual frames or sequences of images, ensuring consistent correction across multiple captures. This method is particularly useful in systems where optical components introduce predictable or measurable distortions, allowing for automated and efficient correction.
6. The method of claim 5 , wherein de-warping the images comprises at least one of distortion correction or chromatic aberration correction.
This invention relates to image processing techniques for correcting distortions in captured images, particularly addressing issues like geometric distortion and chromatic aberration. The method involves de-warping images to improve visual quality by applying at least one of distortion correction or chromatic aberration correction. Distortion correction adjusts the geometric shape of the image to remove unwanted bending or warping caused by lens imperfections or perspective effects. Chromatic aberration correction reduces color fringing by aligning misaligned color channels, ensuring consistent color representation across the image. The process may involve analyzing the image data to identify distortion patterns or color misalignments, then applying mathematical transformations or filtering techniques to correct these issues. The corrected images exhibit improved sharpness, accurate geometry, and true-to-life color reproduction. This method is particularly useful in applications requiring high-fidelity imaging, such as photography, medical imaging, and surveillance systems. The technique enhances image quality by mitigating common optical and processing artifacts, resulting in more accurate and visually pleasing outputs.
7. The method of claim 4 , further comprising: determining a position of the camera relative to an initial position of the camera, wherein the initial position is associated with the sensor data and the images.
8. The method of claim 3 , wherein the sensor data comprises any of global positioning system (GPS) data and barometric data.
9. A system comprising: an aerial vehicle including a camera, a processor, and a memory, the memory including instructions that when executed cause the processor to: determine information associated with the camera, the information including a length of a footprint of the camera and a width of the footprint of the camera, the length of the footprint being based on a horizontal component of a field of view (FOV) and an altitude of the camera and the width of the footprint being based on a vertical component of the field of view (FOV) and the altitude of the camera; determine a localized map based on the information associated with the camera; and overlay the localized map on a vector map, the vector map including geographical information.
10. The system of claim 9 , wherein the vector map further includes at least one of a road network, railroad network, airport, elevation contour, coastline, boundary, or index of geographical name.
11. The system of claim 9 , wherein to determine information associated with the camera of the aerial vehicle comprises to: receive sensor data from the aerial vehicle; determine the altitude of the camera based on the sensor data; determine the information associated with the camera based on the altitude of the camera and the FOV of the camera; and determine the footprint of the camera based on the information associated with the camera.
This invention relates to aerial imaging systems, specifically for determining the coverage area (footprint) of a camera mounted on an aerial vehicle such as a drone or aircraft. The system addresses the challenge of accurately calculating the ground area captured by the camera, which is essential for tasks like aerial surveying, mapping, and inspection. The system receives sensor data from the aerial vehicle, including altitude information, and uses this data to determine the camera's altitude. It then calculates the camera's field of view (FOV) and combines this with the altitude to derive the camera's footprint—the area on the ground that the camera can capture. This allows the system to dynamically adjust imaging parameters based on real-time flight conditions, ensuring optimal coverage and accuracy. The invention improves upon prior methods by integrating sensor data directly into the footprint calculation, reducing reliance on pre-programmed or static assumptions about camera positioning. This dynamic approach enhances the precision of aerial imaging applications, particularly in environments where altitude and other conditions may vary.
12. The system of claim 11 , wherein to determine the localized map based on the information associated with the camera comprises to: receive images from the camera; and determine the localized map based on the images and the footprint of the camera.
A system for generating a localized map using camera data addresses the challenge of accurately mapping environments in real-time for applications such as autonomous navigation, augmented reality, or robotics. The system captures images from a camera and processes these images to create a localized map, which represents the spatial layout of the environment. The camera's footprint, or the area it can effectively capture, is used to define the boundaries and coverage of the map. By analyzing the images in conjunction with the camera's footprint, the system constructs a detailed and precise representation of the surroundings. This approach ensures that the map accurately reflects the environment, accounting for the camera's field of view and limitations. The system may also integrate additional data, such as sensor inputs or pre-existing maps, to enhance accuracy and reliability. The localized map can then be used for navigation, object detection, or other spatial awareness tasks, providing a dynamic and adaptable solution for real-time mapping applications.
13. The system of claim 12 , further causing the processor to: de-warp the images.
A system for processing images, particularly for correcting distortions in captured images, is disclosed. The system includes a processor configured to receive a sequence of images from a camera, where the images may contain distortions such as warping due to lens effects or motion. The processor is further configured to analyze the received images to identify and correct these distortions. Specifically, the system includes a de-warping module that applies geometric transformations to the images to remove warping, ensuring that the output images appear as if they were captured with minimal or no distortion. The de-warping process may involve techniques such as perspective correction, grid-based warping, or other image rectification methods to restore the original shape and alignment of objects in the images. The system may also include additional processing steps, such as noise reduction or sharpening, to enhance image quality after de-warping. This technology is particularly useful in applications where accurate image representation is critical, such as in surveillance, medical imaging, or augmented reality. The system ensures that the final output images are free from distortions, providing a clear and accurate visual representation.
14. The system of claim 13 , wherein to de-warp the images comprises at least one of distortion correction or chromatic aberration correction.
15. The system of claim 12 , further causing the processor to: determine a position of the camera relative to an initial position of the camera, wherein the initial position is associated with the sensor data and the images.
16. A non-transitory computer-readable storage medium comprising stored instructions that, when executed, causes at least one processor to: determine information associated with a camera of an aerial vehicle, the information including a length of a footprint of the camera and a width of the footprint of the camera, the length of the footprint being based on a horizontal component of a field of view (FOV) and an altitude of the camera and the width of the footprint being based on a vertical component of the field of view (FOV) and the altitude of the camera; determine a localized map based on the information associated with the camera; and overlay the localized map on a vector map, the vector map including at least one of a road network, railroad network, airport, elevation contour, coastline, boundary, or index of geographical name.
Unknown
April 13, 2021
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